Feat: add `transform()` function to produce tables with age-wise rows and year-wise columns

[patrickm663]

When dealing with mortality data, it is typical to 'square' it into an $n\times m$ matrix, where entries $m(x,t)$ correspond to the mortality rate for a life aged $x$ in cohort/year $t$.

A function like transform() & transform!() could take in mortality date and apply this transformation. Where there are multiple representations of the mortality data (e.g. males, females, total), a Dict could be returned with DataFrame objects as values, so t["Males"] returns a DataFrame of transformed Male rates. Similarly, a custom struct could work.

[patrickm663]

This will basically be a wrapper for DataFrames.unstack(df, :Year, :Male) but to handle cases where e.g. :Male may be ambiguous and there may be arbitrary columns to handle.